{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Simple Line Plots"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Perhaps the simplest of all plots is the visualization of a single function $y = f(x)$.\n",
    "Here we will take a first look at creating a simple plot of this type.\n",
    "As with all the following sections, we'll start by setting up the notebook for plotting and  importing the packages we will use:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "plt.style.use('seaborn-whitegrid')\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For all Matplotlib plots, we start by creating a figure and an axes.\n",
    "In their simplest form, a figure and axes can be created as follows:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "ax = plt.axes()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In Matplotlib, the *figure* (an instance of the class ``plt.Figure``) can be thought of as a single container that contains all the objects representing axes, graphics, text, and labels.\n",
    "The *axes* (an instance of the class ``plt.Axes``) is what we see above: a bounding box with ticks and labels, which will eventually contain the plot elements that make up our visualization.\n",
    "Throughout this book, we'll commonly use the variable name ``fig`` to refer to a figure instance, and ``ax`` to refer to an axes instance or group of axes instances.\n",
    "\n",
    "Once we have created an axes, we can use the ``ax.plot`` function to plot some data. Let's start with a simple sinusoid:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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P74pVSIige03m4CDgY2aEFCdkCtbtTsbJ5J5VoICDgIdpw317Ppj0iMfjITFK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\nAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f49c348d780>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "ax = plt.axes()\n",
    "\n",
    "x = np.linspace(0, 10, 1000) #1000个点\n",
    "ax.plot(x, np.sin(x));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Alternatively, we can use the pylab interface and let the figure and axes be created for us in the background\n",
    "(see [Two Interfaces for the Price of One](04.00-Introduction-To-Matplotlib.ipynb#Two-Interfaces-for-the-Price-of-One) for a discussion of these two interfaces):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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P74pVSIige03m4CDgY2aEFCdkCtbtTsbJ5J5VoICDgIdpw317Ppj0iMfjITFK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\nAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f49c54df3c8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(x, np.sin(x));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If we want to create a single figure with multiple lines, we can simply call the ``plot`` function multiple times:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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MJnph789nYxaNDOb3e3IoqGwgTN2D3ekSwmSf+8svv3zHY51O1/n3qlWrWLVq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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f49c347f2e8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(x, np.sin(x))\n",
    "plt.plot(x, np.cos(x));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "That's all there is to plotting simple functions in Matplotlib!\n",
    "We'll now dive into some more details about how to control the appearance of the axes and lines."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Adjusting the Plot: Line Colors and Styles"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The first adjustment you might wish to make to a plot is to control the line colors and styles.\n",
    "The ``plt.plot()`` function takes additional arguments that can be used to specify these.\n",
    "To adjust the color, you can use the ``color`` keyword, which accepts a string argument representing virtually any imaginable color.\n",
    "The color can be specified in a variety of ways:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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ICDk5OQQEBNRqt2rVKj7//POav8+ePcvjjz9OUVERf/jDHxg2bJjV6584ccKe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\n0v+i4F5+KwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f49c3299080>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(x, np.sin(x - 0), color='blue')        # specify color by name\n",
    "plt.plot(x, np.sin(x - 1), color='g')           # short color code (rgbcmyk)\n",
    "plt.plot(x, np.sin(x - 2), color='0.75')        # Grayscale between 0 and 1\n",
    "plt.plot(x, np.sin(x - 3), color='#FFDD44')     # Hex code (RRGGBB from 00 to FF)\n",
    "plt.plot(x, np.sin(x - 4), color=(1.0,0.2,0.3)) # RGB tuple, values 0 to 1\n",
    "plt.plot(x, np.sin(x - 5), color='chartreuse'); # all HTML color names supported"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If no color is specified, Matplotlib will automatically cycle through a set of default colors for multiple lines.\n",
    "\n",
    "Similarly, the line style can be adjusted using the ``linestyle`` keyword:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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iBxUS0iOZtjSfvAl2TIL6qgME2tqQfX6M2VlozCbcVVVEXjgXY24uxrw8jCd6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\neaZV5AAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f49c326bfd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(x, x + 0, linestyle='solid')\n",
    "plt.plot(x, x + 1, linestyle='dashed')\n",
    "plt.plot(x, x + 2, linestyle='dashdot')\n",
    "plt.plot(x, x + 3, linestyle='dotted');\n",
    "\n",
    "# For short, you can use the following codes:\n",
    "plt.plot(x, x + 4, linestyle='-')  # solid\n",
    "plt.plot(x, x + 5, linestyle='--') # dashed\n",
    "plt.plot(x, x + 6, linestyle='-.') # dashdot\n",
    "plt.plot(x, x + 7, linestyle=':');  # dotted"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If you would like to be extremely terse, these ``linestyle`` and ``color`` codes can be combined into a single non-keyword argument to the ``plt.plot()`` function:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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YUN/vUDFbhvTPhVd3BLu7syAwkFAvL863b08FCWlhYxLW4q9++w2cnaFRI31v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\nrkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f49c32af5c0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(x, x + 0, '-g')  # solid green\n",
    "plt.plot(x, x + 1, '--c') # dashed cyan\n",
    "plt.plot(x, x + 2, '-.k') # dashdot black\n",
    "plt.plot(x, x + 3, ':r');  # dotted red"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "These single-character color codes reflect the standard abbreviations in the RGB (Red/Green/Blue) and CMYK (Cyan/Magenta/Yellow/blacK) color systems, commonly used for digital color graphics.\n",
    "\n",
    "There are many other keyword arguments that can be used to fine-tune the appearance of the plot; for more details, I'd suggest viewing the docstring of the ``plt.plot()`` function using IPython's help tools (See [Help and Documentation in IPython](01.01-Help-And-Documentation.ipynb))."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Adjusting the Plot: Axes Limits\n",
    "\n",
    "Matplotlib does a decent job of choosing default axes limits for your plot, but sometimes it's nice to have finer control.\n",
    "The most basic way to adjust axis limits is to use the ``plt.xlim()`` and ``plt.ylim()`` methods:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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1qwIiIa0CxKXRvs4Iltrz9hMlFTlhTYCbHcYFSLAn2zSGPRtCR5cG+y/KEBdK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\nAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f49c32c1fd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(x, np.sin(x))\n",
    "\n",
    "plt.xlim(-1, 11)\n",
    "plt.ylim(-1.5, 1.5);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If for some reason you'd like either axis to be displayed in reverse, you can simply reverse the order of the arguments:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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A8qtbkVXejOQJARAIqDOU/CIxxr+/c/Q8dY7ejcFgwOb0coT5umCsanC7Et2J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\nhBCeoEAnhBCe+P/5TkxdcVy1agAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f49c2f96978>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(x, np.sin(x))\n",
    "\n",
    "plt.xlim(10, 0)\n",
    "plt.ylim(1.2, -1.2);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A useful related method is ``plt.axis()`` (note here the potential confusion between *axes* with an *e*, and *axis* with an *i*).\n",
    "The ``plt.axis()`` method allows you to set the ``x`` and ``y`` limits with a single call, by passing a list which specifies ``[xmin, xmax, ymin, ymax]``:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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1qwIiIa0CxKXRvs4Iltrz9hMlFTlhTYCbHcYFSLAn2zSGPRtCR5cG+y/KEBdK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\nAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f49c2fe9ef0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(x, np.sin(x))\n",
    "plt.axis([-1, 11, -1.5, 1.5]);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The ``plt.axis()`` method goes even beyond this, allowing you to do things like automatically tighten the bounds around the current plot:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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P74pVSIige03m4CDgY2aEFCdkCtbtTsbJ5J5VoICDgIdpw317Ppj0iMfjITFK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\nAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f49c2e979b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(x, np.sin(x))\n",
    "plt.axis('tight');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It allows even higher-level specifications, such as ensuring an equal aspect ratio so that on your screen, one unit in ``x`` is equal to one unit in ``y``:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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9oSsVFxfj+eefx65du+Dm5vbAx9RqNRwcHJoVRqvVQqlUNmtdS8UxWwdrG7O1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\nRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f49c2eca588>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(x, np.sin(x))\n",
    "plt.axis('equal');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For more information on axis limits and the other capabilities of the ``plt.axis`` method, refer to the ``plt.axis`` docstring."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Labeling Plots\n",
    "\n",
    "As the last piece of this section, we'll briefly look at the labeling of plots: titles, axis labels, and simple legends.\n",
    "\n",
    "Titles and axis labels are the simplest such labels—there are methods that can be used to quickly set them:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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6autso2/V3h3OLeFCaaV8IWqEMV0COa4r45Te+ruQJCk0YH16AV1bedvcplem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\nkhSEEEIYSVIQQghh9P8B1RUFQAaSetUAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f49c33c87f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(x, np.sin(x))\n",
    "plt.title(\"A Sine Curve\")\n",
    "plt.xlabel(\"x\")\n",
    "plt.ylabel(\"sin(x)\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The position, size, and style of these labels can be adjusted using optional arguments to the function.\n",
    "For more information, see the Matplotlib documentation and the docstrings of each of these functions."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "When multiple lines are being shown within a single axes, it can be useful to create a plot legend that labels each line type.\n",
    "Again, Matplotlib has a built-in way of quickly creating such a legend.\n",
    "It is done via the (you guessed it) ``plt.legend()`` method.\n",
    "Though there are several valid ways of using this, I find it easiest to specify the label of each line using the ``label`` keyword of the plot function:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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C+evrycEBYmPh5EknvviiAlOnXsLZuWD9vFlZWYX697Ik/4f8uVbvGnN/mUti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\niasAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f49c2e5f320>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(x, np.sin(x), '-g', label='sin(x)')\n",
    "plt.plot(x, np.cos(x), ':b', label='cos(x)')\n",
    "plt.axis('equal')\n",
    "\n",
    "plt.legend();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As you can see, the ``plt.legend()`` function keeps track of the line style and color, and matches these with the correct label.\n",
    "More information on specifying and formatting plot legends can be found in the ``plt.legend`` docstring; additionally, we will cover some more advanced legend options in [Customizing Plot Legends](04.06-Customizing-Legends.ipynb)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Aside: Matplotlib Gotchas\n",
    "\n",
    "While most ``plt`` functions translate directly to ``ax`` methods (such as ``plt.plot()`` → ``ax.plot()``, ``plt.legend()`` → ``ax.legend()``, etc.), this is not the case for all commands.\n",
    "In particular, functions to set limits, labels, and titles are slightly modified.\n",
    "For transitioning between MATLAB-style functions and object-oriented methods, make the following changes:\n",
    "\n",
    "- ``plt.xlabel()``  → ``ax.set_xlabel()``\n",
    "- ``plt.ylabel()`` → ``ax.set_ylabel()``\n",
    "- ``plt.xlim()``  → ``ax.set_xlim()``\n",
    "- ``plt.ylim()`` → ``ax.set_ylim()``\n",
    "- ``plt.title()`` → ``ax.set_title()``\n",
    "\n",
    "In the object-oriented interface to plotting, rather than calling these functions individually, it is often more convenient to use the ``ax.set()`` method to set all these properties at once:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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58mXeeeedu/bRp5TMm3y9LoYmHs6yJotCytpZ8J8u3uw9l0ZYVKLS5YhnFLL2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\nHQkFIYQQOv8HJOd3aXm4bD4AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f49c2f63208>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = plt.axes()\n",
    "ax.plot(x, np.sin(x))\n",
    "ax.set(xlim=(0, 10), ylim=(-2, 2),\n",
    "       xlabel='x', ylabel='sin(x)',\n",
    "       title='A Simple Plot');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<!--NAVIGATION-->\n",
    "< [Visualization with Matplotlib](04.00-Introduction-To-Matplotlib.ipynb) | [Contents](Index.ipynb) | [Simple Scatter Plots](04.02-Simple-Scatter-Plots.ipynb) >"
   ]
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}
